Ender Turing Logiciel d'analyse des interactions clients par Lidiia Suslova

Le design Ender Turing Logiciel d'analyse des interactions clients par Lidiia Suslova est un lauréat très estimé du prestigieux 2026 A' Design Award de Fer dans la catégorie Logiciel.

FerLogiciel· 2026

Ender Turing Logiciel d'analyse des interactions clients

par Lidiia Suslova

Client : Ender Turing

Lauréat du A' Design Award de Fer dans la catégorie Logiciel

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Couleurs

Le Design

À propos de Ender Turing Logiciel d'analyse des interactions clients

Ender Turing est une plateforme logicielle en nuage dédiée à l'analyse des conversations du service client. Les appels et les conversations écrites sont évalués automatiquement par l'intelligence artificielle, ce qui allège les procédures d'assurance qualité. Le traitement du langage naturel prend en charge la classification de textes, l'analyse de sentiment, la reconnaissance d'entités, la traduction et la synthèse. Des modèles personnalisés peuvent être créés grâce à une interface de glisser-déposer, et les modèles pré-entraînés peuvent être intégrés à d'autres applications. Des filtres flexibles, des grilles d'évaluation personnalisées et la visualisation des données aident les superviseurs à suivre les interactions.

La Reconnaissance

À propos du A' Design Award de Fer

Ender Turing Logiciel d'analyse des interactions clients est lauréat de l'A' Design Award de Fer, une reconnaissance prestigieuse décernée à de bons designs qui répondent aux exigences professionnelles et industrielles attendues de créations bien conçues. Les lauréats Fer démontrent la grande compétence, la haute spécialisation, la compréhension experte et la capacité créative de leurs créateurs. Ender Turing Logiciel d'analyse des interactions clients est censé être une création très estimée, admirée et chérie, pratique et innovante. Ce design lauréat de l'A' Design Award de Fer intègre les meilleures pratiques de l'industrie et présente des caractéristiques techniques compétentes associées à un savoir-faire et à du talent. Ender Turing Logiciel d'analyse des interactions clients est respecté pour sa rigueur et est conçu pour apporter des améliorations de la qualité de vie qui contribuent à faire du monde un monde meilleur.

Les coulisses du design

Dossier de presse

Crédits, membres de l'équipe et détails techniques fournis par le designer.

Propriétés Uniques: Ender Turing offers unique customer experience solutions, enhancing revenue and loyalty. Real-time analytics on employee-customer interactions empower informed decision-making.

Our AI platform automates QA routines, uncovers business insights, and boosts agent performance through continuous coaching.
Dimensions & Emballage: The core purpose of the Ender Turing engine is to facilitate users in crafting and refining AI models capable of comprehending and generating human-like language. This platform offers a comprehensive suite of Natural Language Processing (NLP) capabilities, encompassing tasks such as text classification, sentiment analysis, entity recognition, language translation, and text summarization, among others. Users have the flexibility to construct tailored models through Ender Turing's intuitive drag-and-drop interface, or seamlessly integrate pre-trained models into their applications via the platform's API.
Mots-Clés: Artificial intelligence, AI, Natural language processing, NLP, Machine learning, ML, Text classification, Sentiment analysis, Data processing, Text summarization, API, Cloud-based platform, Language modeling, Text mining, Call center, Analysis, Scoring
Technologie de Production: Utilizing a data-driven design methodology, we collected feedback by directly observing and interviewing our product's customers. Our decisions were guided by the identification of user pain points and areas of frustration. The outcome is a product solution that effectively addresses the concerns of business. Leveraging insights gained, our solution drives revenue growth by enabling informed decision-making and strategic planning, enhancing business productivity, reducing stress, and offering an intuitive user experience. Moreover, our interface supports over 10 languages, ensuring accessibility and usability across diverse user bases.
Défi de Conception: Experiments were conducted to assess hypotheses and validate design decisions. Our findings revealed that our user base consists largely of non-technical individuals who favor a more prominent communication style. Consequently, we refrain from employing complex logic constructions and cumbersome interface designs. Instead, our UX solutions undergo continual refinement to ensure simplicity and ease of use.
Recherche: Engaging with end users, including data center supervisors and stakeholders, we collected data via interviews, surveys, observations, and competitive analysis. Our key finding is the potential of call center data analysis to boost revenue through invaluable insights for informed decision-making. This approach unveils user and business needs, guiding tailored solutions.
Inspiration: Market Demand: Recognizing the growing need for effective CX solutions in various industries.

Efficiency: Seeking ways to streamline processes within contact centers, QA automation, real-time analysis and revelation business insights.

Customer Satisfaction: Understanding the importance of delivering exceptional customer service to foster loyalty and drive revenue growth.

AI Technology: Leveraging advancements in AI and ML to develop innovative solutions that can adapt and evolve over time.
Durée du Projet: The project commenced its journey in June 2020 in Tallinn, Estonia. Design efforts for the project began in January 2022 and are currently ongoing, with continuous development and enhancement. Notably, the product achieved recognition as the winner at the Latitude59 pitching competition in May 2022, held in Tallinn, Estonia. Additionally, it secured the 2nd place position at the Infoshare Startup Contest in October 2022, hosted in Gdansk, Poland, amidst stiff competition from 500 startups worldwide. Moreover, our team achieved the distinction of Best Seed startup at the Valencia Digital Summit conference in October 2023!
Flux Opérationnel: Our solution offers a 20-fold speed increase in scoring calls and chats, powered by automated AI pre-scoring and quality assurance. It also extracts valuable business insights, allowing users to efficiently monitor interactions with flexible filters. With seamless scorecard customization and robust data visualization tools, informed decision-making is empowered. These capabilities optimize operations and enhance customer experiences, contributing to revenue growth.
Brevets: Scientific publications: 1. Transferability Evaluation of Speech Emotion Recognition Between Different Languages January 2022 DOI:10.1007/978-3-031-04812-8_35 In book: Advances in Computer Science for Engineering and Education (pp.413-426) Ievgen Iosifov Olena Iosifova Oleh Romanovskyi Vladimir Sokolov 2. Automated Pipeline for Training Dataset Creation from Unlabeled Audios for Automatic Speech Recognition July 2021 DOI:10.1007/978-3-030-80472-5_3 In book: Advances in Computer Science for Engineering and Education IV (pp.25-36) Oleh Romanovskyi Ievgen Iosifov Olena Iosifova Vladimir Sokolov 3. Analysis of Automatic Speech Recognition Methods January 2021 Conference: Cybersecurity Providing in Information and Telecommunication SystemsAt: Kyiv, Ukraine Olena Iosifova Ievgen Iosifov Vladimir Sokolov Oleh Romanovskyi Igor Sukaylo 4. Sentence Segmentation from Unformatted Text using Language Modeling and Sequence Labeling Approaches October 2020 DOI:10.1109/PICST51311.2020.9468084 Conference: 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T) Ievgen Iosifov Olena Iosifova Vladimir Sokolov 5. Methods and components of natural language processing August 2020 Adaptive automatic control systems 1(36):93-113 DOI:10.20535/1560-8956.36.2020.209780 Olena Iosifova Ievgen Iosifov Oleksandr Rolik 6. Techniques Comparison for Natural Language Processing June 2020 DOI:10.5281/zenodo.3895814 Conference: 2nd International Workshop on Modern Machine Learning Technologies and Data ScienceAt: Lviv-Shatsk, Ukraine Olena Iosifova Ievgen Iosifov Oleksandr Rolik Vladimir Sokolov
Crédits Images: Lidiia Suslova